Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy

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However, the comparative predictive value of existing histological response scoring systems remains unclear. Methods We retrospectively reviewed 70 patients with stage IV CRCLM who underwent liver resection after neoadjuvant chemotherapy between 2015 and 2021. Pathological response was assessed using two scoring systems: the five-tier Tumor Regression Grade (TRG) by Rubbia-Brandt and the three-tier system proposed by Blazer. Survival analyses were performed using Kaplan–Meier curves, log-rank tests, and Cox regression. Prognostic performance was evaluated through likelihood ratio χ2 tests, trend tests, and area under the ROC curve (AUC) with 95% confidence intervals (CI). Results The median follow-up was 32 months. Median overall survival was 40.1 months in patients with TRG 1–2, 32.1 months for TRG 3, and 18.5 months for TRG 4–5 (p = 0.03). The Rubbia-Brandt TRG score showed good prognostic discrimination with an AUC of 0.80 (95% CI: 0.69–0.90). In contrast, the Blazer score showed no statistically significant survival difference among categories (p = 0.26) and yielded a lower AUC of 0.60 (95% CI: 0.48–0.73). Both the likelihood ratio χ2 (7.41 vs. 2.68) and trend test (p = 0.03 vs. p = 0.09) favored the Rubbia-Brandt system. Conclusions In this series, the Rubbia-Brandt TRG score demonstrated superior prognostic performance compared to the Blazer score for assessing survival after liver resection for CRCLM. These findings support the integration of pathological response scoring into postoperative risk stratification, in combination with classical staging elements. Further validation in larger prospective cohorts is warranted. 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F1000Research 2025, 12 :1523 ( https://doi.org/10.12688/f1000research.135677.3 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] Previously titled: Liver metastases from colorectal carcinoma: performance of pathological response scores Sana ben slama 1 , Ines Mallek https://orcid.org/0009-0009-9269-8365 1 , Nadia Ben Othman 1 , [...] Bochra Bouchabou 2 , Abdelwahab Nakhli https://orcid.org/0000-0002-2511-4069 2 , Mohammed Hajri 3 , Mestiri Hafedh 3 , Ahlem Lahmar 1 , Dhouha Bacha https://orcid.org/0000-0002-8430-0072 1 Sana ben slama 1 , Ines Mallek https://orcid.org/0009-0009-9269-8365 1 , [...] Nadia Ben Othman 1 , Bochra Bouchabou 2 , Abdelwahab Nakhli https://orcid.org/0000-0002-2511-4069 2 , Mohammed Hajri 3 , Mestiri Hafedh 3 , Ahlem Lahmar 1 , Dhouha Bacha https://orcid.org/0000-0002-8430-0072 1 PUBLISHED 29 Aug 2025 Author details Author details 1 Department of Pathology, Centre Hospitalier Universitaire Mongi Slim, La Marsa, Tunis, 2080, Tunisia 2 Department of Gastroenterology, University Hospital Center Mongi Slim, La Marsa, Tunis, 2080, Tunisia 3 Department of Surgery, University Hospital Center Mongi Slim, La Marsa, Tunis, 2080, Tunisia Sana ben slama Roles: Resources, Supervision Ines Mallek Roles: Conceptualization, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Nadia Ben Othman Roles: Formal Analysis, Investigation Bochra Bouchabou Roles: Project Administration Abdelwahab Nakhli Roles: Methodology Mohammed Hajri Roles: Supervision, Validation Mestiri Hafedh Roles: Methodology, Validation Ahlem Lahmar Roles: Supervision, Validation Dhouha Bacha Roles: Methodology, Supervision, Validation OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Background Pathological tumor regression after neoadjuvant chemotherapy is a major prognostic factor in colorectal cancer liver metastases (CRCLM). However, the comparative predictive value of existing histological response scoring systems remains unclear. Methods We retrospectively reviewed 70 patients with stage IV CRCLM who underwent liver resection after neoadjuvant chemotherapy between 2015 and 2021. Pathological response was assessed using two scoring systems: the five-tier Tumor Regression Grade (TRG) by Rubbia-Brandt and the three-tier system proposed by Blazer. Survival analyses were performed using Kaplan–Meier curves, log-rank tests, and Cox regression. Prognostic performance was evaluated through likelihood ratio χ 2 tests, trend tests, and area under the ROC curve (AUC) with 95% confidence intervals (CI). Results The median follow-up was 32 months. Median overall survival was 40.1 months in patients with TRG 1–2, 32.1 months for TRG 3, and 18.5 months for TRG 4–5 (p = 0.03). The Rubbia-Brandt TRG score showed good prognostic discrimination with an AUC of 0.80 (95% CI: 0.69–0.90). In contrast, the Blazer score showed no statistically significant survival difference among categories (p = 0.26) and yielded a lower AUC of 0.60 (95% CI: 0.48–0.73). Both the likelihood ratio χ 2 (7.41 vs. 2.68) and trend test (p = 0.03 vs. p = 0.09) favored the Rubbia-Brandt system. Conclusions In this series, the Rubbia-Brandt TRG score demonstrated superior prognostic performance compared to the Blazer score for assessing survival after liver resection for CRCLM. These findings support the integration of pathological response scoring into postoperative risk stratification, in combination with classical staging elements. Further validation in larger prospective cohorts is warranted. READ ALL READ LESS Keywords Colorectal cancers, Chemotherapy, Surgery, Liver metastases, Regression, Histology, Prognosis, Survival Corresponding Author(s) Ines Mallek ( [email protected] ) Close Corresponding author: Ines Mallek Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 ben slama S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: ben slama S, Mallek I, Ben Othman N et al. Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.12688/f1000research.135677.3 ) First published: 28 Nov 2023, 12 :1523 ( https://doi.org/10.12688/f1000research.135677.1 ) Latest published: 29 Aug 2025, 12 :1523 ( https://doi.org/10.12688/f1000research.135677.3 ) Revised Amendments from Version 2 This revised version of the article includes several key revisions aimed at enhancing clarity and the clinical relevance of findings. First, we clarified the definitions and categorization criteria of the Rubbia-Brandt and Blazer scoring systems, emphasizing their structural differences and implications for interpretation. Second, the Results section now includes updated survival data with clearer stratification by TRG subgroups and corresponding median overall survival estimates. Third, the Discussion has been expanded to provide a more comprehensive interpretation of the prognostic implications of the two grading systems, incorporating relevant literature to contextualize the findings. Finally, the Conclusions have been refined to more directly highlight the clinical value of the Rubbia-Brandt score in risk stratification and postoperative management. These revisions improve the rigor and accessibility of the manuscript for both clinical and academic audiences. This revised version of the article includes several key revisions aimed at enhancing clarity and the clinical relevance of findings. First, we clarified the definitions and categorization criteria of the Rubbia-Brandt and Blazer scoring systems, emphasizing their structural differences and implications for interpretation. Second, the Results section now includes updated survival data with clearer stratification by TRG subgroups and corresponding median overall survival estimates. Third, the Discussion has been expanded to provide a more comprehensive interpretation of the prognostic implications of the two grading systems, incorporating relevant literature to contextualize the findings. Finally, the Conclusions have been refined to more directly highlight the clinical value of the Rubbia-Brandt score in risk stratification and postoperative management. These revisions improve the rigor and accessibility of the manuscript for both clinical and academic audiences. To read any peer review reports and author responses for this article, follow the "read" links in the Open Peer Review table. READ REVIEWER RESPONSES Introduction Colorectal cancer (CRC) ranks third globally in terms of the most commonly diagnosed cancer and second as the leading cause of cancer-related deaths. 1 CRC progression typically involves metastatic spread, with the liver being the most frequently affected site. Synchronous liver metastases (LM) occur in approximately 20% of patients, while nearly 50% will develop them during the course of their illness. 2 Surgical resection is considered the most effective treatment option for LM, but only a subset of patients are candidates for resection, depending on factors such as tumor size, number, location, and liver function. Neoadjuvant chemotherapy (CT) significantly improves the prognosis of resectable cases and can make initially unresectable lesions amenable to surgery. 3 The pathological response of LM to neoadjuvant therapy is a crucial prognostic factor for recurrence and survival. The Rubbia-Brandt et al. score 4 was one of the earliest established to evaluate tumor response to therapy, and other scores, such as the one proposed by Blazer et al., have also been suggested. 5 However, no standardized scoring system currently exists, and studies comparing the performance of different scores are still lacking. This study aims to assess tumor response in liver resection specimens histologically, based on the Rubbia-Brandt and Blazer scores after neoadjuvant treatment, and compare the prognostic performance of these two scoring systems. Methods Ethics and consent The Ethics Committee for Mongi Slim Hospital La Marsa has examined the study and protocol of the following project: “Liver Metastases From Colorectal Carcinoma: Performance of Pathological Response Scores”. It was made and presented by Dr. MALLEK Ines (Department of anatomopathology). The project does not raise any particular ethical problem. The ethics approval was given prior to the start of the study in 2021, in French, as Tunisia is a mainly French speaking country. An updated ethics approval was also provided in English for the purposes of the f1000 submission. The approval was registered under number 43/2021 in French version and 27/2023 in English version. Participated in this meeting: PR Lamia BEN JEMAA, Ethics Committee President Mongi Slim Hospital of Marsa and PR Mohamed Sami MEBAZAA. Study design: This study was a retrospective, and longitudinal analysis of a single-center series of patients with CRCLM who underwent surgery after neo-adjuvant treatment. All cases were collected from the department of Pathology of the University hospital in north Tunisia (Hospital Mongi Slim) between January 2015 and June 2021. Study population: We included patients who met the following criteria: Diagnosis of CRCLM and underwent surgical treatment after neo-adjuvant CT and availability of a detailed anatomical-pathological report. We excluded patients who: Had cancer in another organ, underwent surgery without neo-adjuvant CT. Additionally, patients whose hospital records were unusable or could not be found, and cases with non-usable slides or tissue blocks were excluded from the study. Patients who received other neo-adjuvant treatments (hepatic intra-arterial CT or percutaneous radiofrequency) were also excluded. Data collection : We collected epidemiological, clinical, and biological data, as well as information on primary CRC, CRCLM, types of neo-adjuvant therapy initiated, type of surgical procedure performed, follow-up, and outcome for all patients included in the study. Pathological study: Based on the pathology report, we recorded the location, number, and size of the CRCLM. All slides were reviewed by two senior pathologists. We assessed the degree of tumor response or Tumor Regression Grading (TRG) according to: The Rubbia-Brandt score 4 and the Blazer score. 5 We also recorded the following tumor characteristics: The state of the resection margins (R0 if safe or R1 if less than 1mm), the presence or absence of vascular emboli, and endobiliary extension. Statistical analysis: The data was entered using SPSS® version 24.0. Descriptive and analytical studies were conducted. Mortality was assessed by actuarial survival curves using the Kaplan Meier model. The comparison of survival curves was performed by the Log Rank test. The performance of each score was assessed by the following criteria: homogeneity, monotonicity, and discriminatory capacity. The significance level was set at 0.05. 6 , 7 Results Study characteristics We included 70 patients in our study. 48 were male (69%), giving a sex ratio (males/females) of 2.2. The average age of the patients was 56 years. In 54 cases (77%) it was a colon cancer, in 16 cases (23%) rectal cancer. In 64 cases (92%), it was adenocarcinoma without other specifications (SAI). We found five cases of mucinous adenocarcinoma (7%), and only one case of adenosquamous carcinoma. The SAI adenocarcinomas were all low grade. The most frequent stage at diagnosis was stage IV with synchronous metastases, all of which were in the liver (40 cases, 57%). All patients underwent carcinological surgical resection according to the initial tumour site. Time to onset of liver metastases: Forty patients (57%) had at least one synchronous LM. Thirty patients (43%) had metachronous LM. The mean time to onset of metachronous LM was 10 months. Neo-adjuvant treatment modalities: Of our patients, 47 received CT alone (67%) and 23 received CT plus targeted therapy (33%). The most represented CT regimen was FOLFOX (Folinic acid + 5FU + Oxaliplatin), used in 63 patients (90%). The average number of courses administered was estimated at 6 courses (extremes between 2 and 12 courses). Surgical treatment of liver metastases: CRCLMs were bi-lobar in 63% of cases (44 cases) and uni-lobar in 37% (26 cases). Anatomical hepatectomy (lobectomy/segmentectomy) was performed in 28 cases (40%) and non-anatomical (metastasectomy or wedge resection) in 42 cases (60%). Pathological characteristics of liver metastases: The average number of LMs was three (extremes of 1 to 12 per patient) and the mean lesion size was 25 mm (range 2-130 mm). The LMs were in 43% (30 cases) in the right lobe and in 20% (14 cases) in the left lobe. They were bi-lobar in 37% of cases (26 cases). According to Rubbia-Brandt score, the CRCLMs were classified into TRG 1 in eight cases (11%), TRG 2 in eight cases (11%), TRG 3 in 17 cases (24%), TRG 4 in 30 cases (43%), TRG 5 in seven cases (10%). And according to Blazer, five patients (7%) had a complete pathological response, 34 patients (49%) had a minor response and 31 (44%) had a major response. The resection margins of LM were R0 in 59 resection pieces (77%) and invaded (R1) in 11 cases (16%). We also found vascular emboli in six patients (9%). Only one patient had endo-biliary extension. Moreover, Six of the 45 patients had lymph node metastases ( Figures 2 and 3 ). Microscopic examination of the liver parenchyma remote from the CRCLMs showed the presence of chemo-induced lesions in 42 patients (60%): 18 cases (26%) of vascular lesions (sinusoidal obstruction syndrome), 13 cases of steatosis (19%), one case of steatohepatitis and 10 cases with associated lesions (14%). Study analysis of survival and performance of TRG scores Overall survival for all stages was 85.5% at 12 months, 41.7% at 24 months and 19.3% at 36 months. There was a significant difference in survival between the different grades for Rubbia- Brandt TRG (p=0.03) but not for Blazer TRG (p=0.269). For Rubbia-Brandt TRG, the median survival was better in the case of a major response (TRG 1/TRG 2) assessed at 40.1 and 41.1 months after the initial diagnosis. In the case of partial response (TRG 3), the median survival was 32.1 months. In cases of no response (TRG 4/TRG 5), survival was estimated at 29.9 and 18.5 months. For Blazer, the median survival was greater for complete response, estimated at 41.1 months after initial diagnosis. For the major response group, survival was estimated at 38.2 months. For the minor or no response group, survival was 29.3 months. When discussing homogeneity, the likelihood ratio χ 2 (LR) for The Rubbia- Brandt TRG had the highest LR+. Rubbia-Brandt has a score of 10.953 and Blazer has a score of 7.246. The RV+ of the Rubbia-Brandt score was greater than 10, so it is a score with very strong diagnostic contribution. The RV+ of the Blazer score was between 5 and 10, so it is a score with strong diagnostic input. When looking at monotonicity with the linear trend χ 2 , of the two scores, the Rubbia-Brandt TRG had the highest linearity value. Rubbia-Brandt has a score of 10.738 and Blazer has a score of 4.446. Looking at the Discriminatory capacity, we can see a sensitivity and specificity of scores for survival prediction. The graphical representation of the predictive capacity of each score for survival is the AUC of the ROC curve is as follows the Figure 1 . The Rubbia-Brandt score was a good performing score as its AUC under the ROC curve was 0.8. The Blazer score was a poorly performing score as its AUC under the ROC curve was 0.6. The Rubbia-Brandt TRG score was better at predicting survival than the Blazer score (p=0.003). Figure 1. ROC Curve for Rubbia Brandt and Blazer scores. Figure 2. Liver metastasis with tumour regression posing a problem between the two scores: partial/complete. Predominant fibrosis with scattered residual tumour cells: According to Rubbia-Brandt, partial response (TRG 3) and according to Blazer, this is a major pathological response (presence of 1 to 49% residual tumour cells) (HEx20). Figure 3. Liver metastasis with major or partial tumour regression, according to the scores. Abundant fibrosis and rare residual carcinomatous structures (arrow). According to Blazer, this is a major pathological response and TRG2 according to Rubbia-Brandt (HEx25). Discussion In this retrospective study of 70 patients with colorectal cancer liver metastases (CRCLM), the average age was 56 years with a male-to-female ratio of 2.2. A total of 57% of patients presented with synchronous liver metastases (LM) at diagnosis. Pathological response was assessed using two scoring systems: the five-tier Rubbia-Brandt Tumor Regression Grade (TRG) and the three-tier Blazer score. According to the Rubbia-Brandt TRG, 11% of metastases were classified as TRG 1, 11% as TRG 2, 24% as TRG 3, 40% as TRG 4, and 10% as TRG 5. Using the Blazer score, 7% of cases had a complete pathological response, 44% showed a major response, and 49% a minor response. Overall survival was 85.5% at 12 months, 41.7% at 24 months, and 19.3% at 36 months. As expected, patients with a major or complete pathological response had longer median survival than those with partial or no response. The Rubbia-Brandt TRG demonstrated superior predictive performance for survival, with an area under the curve (AUC) of 0.8 on ROC analysis, compared to 0.6 for the Blazer score. It also exhibited higher diagnostic contribution (RV+ >10) and better linearity (10.73). These results suggest that the Rubbia-Brandt TRG, through its detailed five-level assessment based on tumor cell regression and fibrosis, may be more accurate in reflecting treatment response and correlating with survival. Limitations: This study presents several limitations. Its retrospective design, combined with incomplete clinical data and treatment heterogeneity, may have influenced therapeutic responses and survival outcomes. The absence of inter-observer variability assessment for both TRG systems is another important limitation. Prognostic factors in CRCLM: Multiple prognostic variables are known to impact outcomes in CRCLM. These include the timing of LM occurrence, response to neoadjuvant chemotherapy (CT), number and size of metastases (tumors >10 cm are associated with poor prognosis) 8 , and quality of surgical resection. 9 Histopathological invasion factors also correlate with reduced overall survival. 10 , 11 While radiological assessment using RECIST criteria remains standard, 12 studies show it does not always align with survival, particularly after targeted therapy with cytostatic effects. 13 In contrast, pathological evaluation of the resection specimen more accurately reflects systemic therapy response. 13 , 14 Additionally, chemotherapy-induced liver injury significantly affects prognosis. 3 Rubbia-Brandt TRG system: First proposed in 2006, the Rubbia-Brandt score 4 was adapted from Mandard’s system 12 for rectal and esophageal cancers. It defines five TRG categories based on the ratio of residual tumor cells to fibrosis: TRG1 (complete fibrosis), TRG2 (predominant fibrosis with rare tumor cells), TRG3 (fibrosis with more tumor cells), TRG4 (predominant tumor cells), and TRG5 (no fibrosis, only tumor). Necrosis is excluded, as it may reflect spontaneous tumor degeneration rather than chemotherapy-induced regression. In the original study, 4 patients receiving neoadjuvant CT had significantly better pathological regression than those undergoing surgery alone (p < 0.0001). Five-year survival was 41% for TRG 1–2, 38% for TRG 3, and only 9% for TRG 4–5. In our cohort, we observed similar TRG distributions and confirmed the prognostic value of near-complete and partial responses. Importantly, this system aligns with the American Joint Committee on Cancer (AJCC) recommendations for primary tumors, enabling direct comparison between primary CRC and metastases. Nonetheless, TRG2 remains imprecise due to the subjective notion of “rare residual tumor cells.” Introducing defined percentage thresholds could improve reproducibility. 15 Moreover, using two parameters (tumor cells and fibrosis) may complicate routine implementation. Alternative approaches like the PRG (Pathological Response Grade), which relies solely on the percentage of viable tumor cells, have shown prognostic utility 16 but require further validation. Another limitation is the lack of integration of modern targeted therapies in the original Rubbia-Brandt study. Agents like bevacizumab or cetuximab, widely used today, may alter tumor response patterns. 17 Blazer score: In 2008, Blazer et al. 5 proposed a simplified three-tier regression system based on residual viable tumor cells: complete response (0%), major response (1–49%), and minor response (≥50%). The score averages responses across multiple metastases, which may dilute heterogeneity. In our study, complete response was observed in 7% of patients, major in 44%, and minor in 49%. Blazer et al. reported 5-year survival rates of 75%, 56%, and 33% for complete, major, and minor responders, respectively. While we observed better survival in complete responders, statistical differences between groups were not significant. This score, while simple, has limitations. Its reliance on estimating initial tumor area introduces variability, and its 50% threshold may lack sensitivity. Additionally, fibrosis or necrosis can occur in untreated tumors, complicating interpretation. 4 Performance of the scores: No prior studies have directly compared the performance of pathological regression scores for CRCLM. Our findings suggest that the Rubbia-Brandt TRG outperforms the Blazer score in prognostic accuracy. With an AUC of 0.8, higher RV+, and greater linearity, it offers more granularity in assessing tumor regression and survival correlation. 18 However, both systems present challenges, especially in interpreting intermediate categories. The “almost complete regression” category is subjective. TRG 3, defined as “residual tumor cells scattered in fibrotic tissue”, 4 overlaps with the Blazer “major response” (<50% viable tumor), 5 yet their clinical implications may differ. Importantly, neither score accounts adequately for intra-tumoral heterogeneity. The Rubbia-Brandt system considers only the worst lesion, while the Blazer score averages across all metastases. Evidence suggests that the presence of at least one LM with complete regression is associated with improved prognosis. 19 , 20 Thus, reporting individual TRG scores for each lesion may enhance prognostic precision. Perspectives and recommendations: A robust and standardised pathological response system is essential for evaluating resected CRCLM. Future prospective studies with large cohorts should aim to harmonise macroscopic sampling protocols, assess inter-observer reproducibility, and integrate TRG with other histopathological variables in predictive algorithms. Given its superior performance in our study, the Rubbia-Brandt TRG should be incorporated into routine pathology reports for resected CRCLMs following neoadjuvant therapy. Used alongside ypTN staging, it provides valuable prognostic information and could inform clinical decision-making. 21 Multicentric studies are warranted to validate these findings and further refine pathological assessment strategies. Conclusion In conclusion, surgical resection remains the gold standard treatment for CRCLM, and the prognosis is significantly improved with the use of neoadjuvant chemotherapy (CT). Pathological response to neo-adjuvant therapy is a crucial prognostic factor correlated with recurrence and survival. The Rubbia Brandt TRG system can complement the ypTN stage and other pathological criteria to improve the predictivity of survival. Data availability Figshare. Data Liver Metastases From Colorectal Carcinoma: Performance Of Pathological Response Scores. DOI: https://doi.org/10.6084/m9.figshare.23620656.v1 . 21 Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC BY 4.0 Public domain dedication). References 1. Cervantes A, Adam R, Roselló S, et al. : Metastatic colorectal cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann. Oncol. 2023; 34 (1): 10–32. PubMed Abstract | Publisher Full Text 2. Mella J, Biffin A, Radcliffe AG, et al. : Population-based audit of colorectal cancer management in two UK health regions. Colorectal cancer working group, royal college of surgeons of England clinical epidemiology and audit unit. Br. J. Surg. 1997 Dec; 84 (12): 1731–1736. Publisher Full Text 3. Passot G, Soubrane O, Giuliante F, et al. : Recent advances in chemotherapy and surgery for colorectal liver metastases. Liver Cancer. 2016 Nov; 6 (1): 72–79. PubMed Abstract | Publisher Full Text 4. Rubbia-Brandt L, Giostra E, Brezault C, et al. : Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann. Oncol. 2007; 18 (2): 299–304. PubMed Abstract | Publisher Full Text 5. Blazer DG, Kishi Y, Maru DM, et al. : Pathologic response to preoperative chemotherapy: a new outcome end point after resection of hepatic colorectal metastases. J. Clin. Oncol. 2008 Nov; 26 (33): 5344–5351. PubMed Abstract | Publisher Full Text 6. Ueno S, Tanabe G, Sako K, et al. : Discrimination value of the new western prognostic system (CLIP score) for hepatocellular carcinoma in 662 japanese patients. Cancer of the liver italian program. Hepatology. 2001 Sep; 34 (3): 529–534. PubMed Abstract | Publisher Full Text 7. Swets JA: Measuring the accuracy of diagnostic systems. Science. 1988 Jun; 240 (4857): 1285–1293. Publisher Full Text 8. Phelip JM, Tougeron D, Léonard D, et al. : Metastatic colorectal cancer (mCRC): french intergroup clinical practice guidelines for diagnosis, treatments and follow-up (SNFGE, FFCD, GERCOR, UNICANCER, SFCD, SFED, SFRO, SFR). Dig. Liver Dis. 2019 Oct; 51 (10): 1357–1363. PubMed Abstract | Publisher Full Text 9. Tharin Z, Blanc J, Alaoui IC, et al. : Influence of primary tumor location and resection on survival in metastatic colorectal cancer. World J. Gastrointest Oncol. 2020 Nov; 12 (11): 1296–1310. PubMed Abstract | Publisher Full Text | Free Full Text 10. Chun YS, Vauthey JN, Boonsirikamchai P, et al. : Association of computed tomography morphologic criteria with pathologic response and survival in patients treated with bevacizumab for colorectal liver metastases. J. Am. Med. Assoc. 2009 Dec; 302 (21): 2338–2344. PubMed Abstract | Publisher Full Text | Free Full Text 11. Reddy SK, Parker RJ, Leach JW, et al. : Tumor histopathology predicts outcomes after resection of colorectal cancer liver metastases treated with and without pre-operative chemotherapy. J. Surg. Oncol. 2016 Mar; 113 (4): 456–462. PubMed Abstract | Publisher Full Text 12. Bouzourene H, Bosman FT, Seelentag W, et al. : Importance of tumor regression assessment in predicting the outcome in patients with locally advanced rectal carcinoma who are treated with preoperative radiotherapy. Cancer. 2002 Feb; 94 (4): 1121–1130. PubMed Abstract | Publisher Full Text 13. Viganò L, Capussotti L, De Rosa G, et al. : Liver resection for colorectal metastases after chemotherapy: impact of chemotherapy-related liver injuries, pathological tumor response, and micrometastases on long-term survival. Ann. Surg. 2013 Nov; 258 (5): 731–742. Publisher Full Text 14. Cai Y, Lu X, Zhu X, et al. : Histological tumor response assessment in colorectal liver metastases after neoadjuvant chemotherapy: impact of the variation in tumor regression grading and peritumoral lymphocytic infiltration. J. Cancer. 2019 Oct; 10 (23): 5852–5861. PubMed Abstract | Publisher Full Text | Free Full Text 15. Baldin P, Van Den Eynde M, Hubert C, et al. : The role of the pathologist and clinical implications in colorectal liver metastasis. Acta Gastroenterol. Belg. 2018 Jul; 81 (3): 419–426. 16. Tomasello G, Petrelli F, Ghidini M, et al. : Tumor regression grade and survival after neoadjuvant treatment in gastro- esophageal cancer: a meta-analysis of 17 published studies. Eur. J. Surg. Oncol. 2017 Sep; 43 (9): 1607–1616. PubMed Abstract | Publisher Full Text 17. Kong JC, Guerra GR, Warrier SK, et al. : Prognostic value of tumour regression grade in locally advanced rectal cancer: a systematic review and meta-analysis. Color. Dis. 2018 Jul; 20 (7): 574–585. PubMed Abstract | Publisher Full Text 18. Chan G, Hassanain M, Chaudhury P, et al. : Pathological response grade of colorectal liver metastases treated with neoadjuvant chemotherapy. HPB. 2010 May; 12 (4): 277–284. PubMed Abstract | Publisher Full Text | Free Full Text 19. Nordlinger B, Adam R, Arnold D, et al. : The role of biological agents in the resection of colorectal liver metastases. Clin. Oncol. 2012 Aug; 24 (6): 432–442. Publisher Full Text 20. Poultsides GA, Bao F, Servais EL, et al. : Pathologic response to preoperative chemotherapy in colorectal liver metastases: fibrosis, not necrosis, predicts outcome. Ann. Surg. Oncol. 2012 Sep; 19 (9): 2797–2804. Publisher Full Text 21. Mallek I: Data Liver Metastases From Colorectal Carcinoma: Performance Of Pathological Response Scores. figshare. [Dataset]. 2023. Publisher Full Text Comments on this article Comments (0) Version 3 VERSION 3 PUBLISHED 28 Nov 2023 ADD YOUR COMMENT Comment Author details Author details 1 Department of Pathology, Centre Hospitalier Universitaire Mongi Slim, La Marsa, Tunis, 2080, Tunisia 2 Department of Gastroenterology, University Hospital Center Mongi Slim, La Marsa, Tunis, 2080, Tunisia 3 Department of Surgery, University Hospital Center Mongi Slim, La Marsa, Tunis, 2080, Tunisia Sana ben slama Roles: Resources, Supervision Ines Mallek Roles: Conceptualization, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Nadia Ben Othman Roles: Formal Analysis, Investigation Bochra Bouchabou Roles: Project Administration Abdelwahab Nakhli Roles: Methodology Mohammed Hajri Roles: Supervision, Validation Mestiri Hafedh Roles: Methodology, Validation Ahlem Lahmar Roles: Supervision, Validation Dhouha Bacha Roles: Methodology, Supervision, Validation Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (3) version 3 Revised Published: 29 Aug 2025, 12:1523 https://doi.org/10.12688/f1000research.135677.3 version 2 Revised Published: 29 Nov 2024, 12:1523 https://doi.org/10.12688/f1000research.135677.2 version 1 Published: 28 Nov 2023, 12:1523 https://doi.org/10.12688/f1000research.135677.1 Copyright © 2025 ben slama S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article ben slama S, Mallek I, Ben Othman N et al. Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.12688/f1000research.135677.3 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 3 VERSION 3 PUBLISHED 29 Aug 2025 Revised Views 0 Cite How to cite this report: Sturesson C. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.185719.r410779 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v3#referee-response-410779 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 29 Sep 2025 Christian Sturesson , Karolinska University, Stockholm, Sweden Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.185719.r410779 The authors present an interesting study on the impact of neoadjuvant chemotherapy on survival after resection of colorectal liver metastases. Based on the histological response of chemotherapy, the authors show an association between survival and histological response, showing an advantage ... Continue reading READ ALL The authors present an interesting study on the impact of neoadjuvant chemotherapy on survival after resection of colorectal liver metastases. Based on the histological response of chemotherapy, the authors show an association between survival and histological response, showing an advantage of the Rubbia-Brandt system. My biggest concern is that there are very few patients in each group making it difficult to draw firm conclusions about the causality of pathological response and survival. If the cohort was bigger, a multivariable analysis would also be needed to define which parameters influence survival. I'm afraid that the small number of patients make the results too unreliable. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: HBP-surgery I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Sturesson C. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.185719.r410779 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v3#referee-response-410779 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 2 VERSION 2 PUBLISHED 29 Nov 2024 Revised Views 0 Cite How to cite this report: Hull M. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r353171 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-353171 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 03 Jan 2025 Mark Hull , Leeds Institute of Medical Research, University of Leeds, Leeds, UK Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.171278.r353171 This is a small retrospective series of cases undergoing neo-adjuvant chemotherapy before CRCLM surgery. Cases were classified according to two published scoring systems for neo-adjuvant chemotherapy response. I did not find that the results provided a significant ... Continue reading READ ALL This is a small retrospective series of cases undergoing neo-adjuvant chemotherapy before CRCLM surgery. Cases were classified according to two published scoring systems for neo-adjuvant chemotherapy response. I did not find that the results provided a significant contribution to the field and the methods used are still unclear despite previous comments from other Reviewers. There was no CONSORT-style diagram explaining exclusions and number of CRCLM cases without neo-adjuvant treatment. I also could not access any Kaplan-Meier curves mentioned in amendments from V1. It is unclear about the profile of cases with conflicting information about the stage IV cases in the text and Abstract. A table may be helpful for the reader to interpret the range of TRG and Blazer scores. Several references are very old and could be updated. Similar to other reviewers, I could not understand how the ROC analysis was performed on scoring systems with >/= three grades. I suggest formal statistical review to confirm appropriateness and correct methodology for assessment of the scoring system characteristics. The statement about cases with lymph node metastasis was unclear. The Discussion is far too long and repeats many of the results. In parts, it reads like a narrative review of the literature. The Conclusion section does not contain any novel finding and the data provided do not support the statement that the Rubbia-Brandt TRG score can complement TN stage for improved survival prediction. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? No Competing Interests: No competing interests were disclosed. Reviewer Expertise: Trialist investigating pre-operative and adjuvant therapy in CRCLM resection surgery patients I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Hull M. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r353171 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-353171 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Peoples J. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r345538 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-345538 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 26 Dec 2024 Jacob Peoples , Queen's University, Kingston, Canada Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.171278.r345538 The paper “Liver metastases from colorectal carcinoma: performance of pathological response scores” by Ben Slama et al. provides a comparison of two pathological response evaluation criteria for scoring response to neoadjuvant chemotherapy in patients undergoing hepatic resection for colorectal liver ... Continue reading READ ALL The paper “Liver metastases from colorectal carcinoma: performance of pathological response scores” by Ben Slama et al. provides a comparison of two pathological response evaluation criteria for scoring response to neoadjuvant chemotherapy in patients undergoing hepatic resection for colorectal liver metastases—the Rubbia-Brandt score, and the Blazer scoring system. The scores are evaluated in terms of their prognostic ability in terms of overall survival after surgery. My primary concern about the study is that it lacks details that would aid in evaluating the results. In particular, I feel that the statistical analysis is described too briefly. The exact procedures used to conduct the statistical tests should be described, so that a reader could reproduce the analysis given the data table. For example, AUC is a metric for a binary outcome – what was the procedure for treating overall survival as binary? Likelihood ratios and RV scores are general tools that can be applied to many things in many ways. It should be described specifically how they are used to measure homogeneity and monotonicity in this context. On the topic of statistical analysis, why use AUC as a measure of discriminative ability rather than something more directly applicable to survival data such as the C-index? 1 I also want to raise a few possible reporting errors in the Study Characteristics section of the results: Under “Surgical treatment of liver metastases” it is stated that 63% were bilobar, and 37% uni-lobar. A few lines later, under “Pathological characteristics of liver metastases” it is stated that they were bi-lobar in 37% of cases (opposite of previous sentence). Please ensure all reported statistics are correct and internally consistent. Finally, I agree with many of the previous reviewers’ points, many of which are not yet addressed. These would include: A consort diagram would be helpful Include Kaplan-Meier curves of overall survival of entire cohort, as well as breakdown across different score categories so that the difference in separation between the two scoring systems can be visually compared? Much of the discussion feels irrelevant to the results of the paper. It would be better to have less survey-like content, and more discussion of how the findings of this paper add or contribute to the existing literature. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? No If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes References 1. Harrell F: Evaluating the Yield of Medical Tests. JAMA: The Journal of the American Medical Association . 1982; 247 (18). Publisher Full Text Competing Interests: No competing interests were disclosed. Reviewer Expertise: medical image analysis, colorectal liver metastases I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Peoples J. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r345538 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-345538 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 28 Nov 2023 Views 0 Cite How to cite this report: Rajendran L and Magyar C. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r278480 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-278480 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 21 May 2024 Luckshi Rajendran , Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada Christian Magyar , Multi-Organ Transplant Program, University Health Network (Ringgold ID: 7989), Toronto, Ontario, Canada; Department of Visceral Surgery and Medicine, Bern University Hospital, Bern, Switzerland Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.148808.r278480 This article by Ben Slama et al., provides a retrospective review of the performance of two prognostic scoring system based on assessment of pathologic response following neoadjuvant chemotherapy and liver resection for colorectal liver metastases. We would like to commend ... Continue reading READ ALL This article by Ben Slama et al., provides a retrospective review of the performance of two prognostic scoring system based on assessment of pathologic response following neoadjuvant chemotherapy and liver resection for colorectal liver metastases. We would like to commend the authors for their efforts; however, we would like to raise the following points/ concerns: Abstract: 1. For the sex ratio, the comparator is needed, otherwise unable to deduce without assumption. Alternatively mentioning % of males (or alternatively females) could be considered. 2. Background and methods imply that all have tumors are stage IV (i.e. CRLM) – is 57% meant to indicate synchronous, and rest is metachronous? This is unclear/ inaccurate -should be rephrased. Similarly, the next sentence referencing “all stages combined” is confusing - these theoretically are all stage IV disease 3. Please incorporate statistical significance in comparison for survival estimates based on TRG1-5. Also, why do you use mean (overall?) survival and not median? 4. Please show 95%CI of the AUC. 5. Conclusions/Discussion section is missing in the abstract. Introduction: 1. Global disease burden (i.e. first sentence): we recommend to reference the original data source from WHO from the global cancer observatory 2. This paragraph needs to be proofread – grammar/ missing words, does not flow overall 3. Please add a statement on resectability considerations of CRLM, especially given only subset of patients are resection candidates 4. We recommend implementing guideline references (e.g. [Ref-1] ) and the original references for the neoadjuvant trials 5. The gap in knowledge statement needs to be rephrased, because of lack of accuracy. Methods: 1. Please include the different neoadjuvant chemotherapy treatment regimens and dosages. Additionally, RFA for CRLM is not considered a neoadjuvant treatment – it can be used in realm of curative. I would focus solely on neoadjuvant chemotherapy in this paper. Similarly use of HAIP may be a different population of patients with initially unresectable disease, can be confusing also when lumped in with population that received IV chemo alone 2. Please include last date of follow-up included. 3. Was normality of data distribution assessed? 4. Which statistical test were used to compare pathological responses? Please write in more detail about your diagnostic performance analysis, which tests were used? 5. For survival analysis we recommend to read [Ref-2,3]. Results: 1. How many left sided vs. right-sided tumours; Please also include other factors like presence of RAS mutation, BRAF status? 2. Is this all liver-only mets (i.e. extrahepatic mets excluded)? What is the percent of major vs. minor hepatectomy? What was done with the primary tumour in all of these cases? 3. Please consider including a CONSORT diagram, to allow the reader to assess the potential degree of selection bias, as you excluded patients based on ‘hospital records were unusable or could not be found, and cases with non-usable slides or tissue blocks’. 3. Same here as within the abstract, was 57% synchronous and 43% metachronous? Otherwise your selection criteria are not coherent. 4. Figure 1 and figure 2 are mixed up in the manuscript. Please fix 5. Consider reporting the T, N and M status of your cohort. 6. Please consider including the Kaplan Meier curve stratified by your regression grades. 7. Same here, why do you report mean survival and not median survival? Discussion: 1. Too long, reads like a review, please consider restricting it to what is related to this study. Consider restructuring into five paragraphs with: (1) key findings, (2) strengths and limitations, (3) comparison with similar research, (4) explanations of findings and (5) implications and actions needed. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? No If applicable, is the statistical analysis and its interpretation appropriate? No Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? No References 1. Cervantes A, Adam R, Roselló S, Arnold D, et al.: Metastatic colorectal cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol . 2023; 34 (1): 10-32 PubMed Abstract | Publisher Full Text 2. Clark TG, Bradburn MJ, Love SB, Altman DG: Survival analysis part I: basic concepts and first analyses. Br J Cancer . 2003; 89 (2): 232-8 PubMed Abstract | Publisher Full Text 3. Austin PC, Lee DS, Fine JP: Introduction to the Analysis of Survival Data in the Presence of Competing Risks. Circulation . 2016; 133 (6): 601-9 PubMed Abstract | Publisher Full Text Competing Interests: No competing interests were disclosed. Reviewer Expertise: clinical epidemiology, transplantation, liver cancer, surgery We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Rajendran L and Magyar C. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r278480 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-278480 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Brahimi M and Yassine B. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r227155 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-227155 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 20 Dec 2023 Maroua Brahimi , Laboratory of Pathology, Centre hospitalier mohamed V, Safi, Marrakech-safi, Morocco Belghali Yassine , Centre hospitalier universitaire mohamed VI, Marrakech, Marrakech, Morocco Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.148808.r227155 In the paper " Liver metastases from colorectal carcinoma: performance of pathological response scores", the authors evaluate the pathological response and compare the performance of two prognostic scores : Rubbia-Brandt tumor regression grade (TRG) and the Blazer scoring system, in ... Continue reading READ ALL In the paper " Liver metastases from colorectal carcinoma: performance of pathological response scores", the authors evaluate the pathological response and compare the performance of two prognostic scores : Rubbia-Brandt tumor regression grade (TRG) and the Blazer scoring system, in a population of 70 patients with liver metastases from colorectal cancer . The conclusion is that the Rubbia-Brandt TRG was better in predicting survival, which is well known.The study is not novel and the aim of the study isn't contibutive to the field (1). Overall, the precision of the manuscript does not reach the acceptable standards, there are so many methodological errors: How the specimen was prepared? How the cases with more than one liver metastase were evaluated?.......(1), (2). Many sources of heterogenicity: for example all the histologic types were included....The statistical results lacks clarity and representativity (tables, figures...) (1). Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? Partly References 1. Rubbia-Brandt L, Giostra E, Brezault C, Roth AD, et al.: Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann Oncol . 2007; 18 (2): 299-304 PubMed Abstract | Publisher Full Text 2. Wang Y, Yuan YF, Lin HC, Li BK, et al.: Pathologic response after preoperative therapy predicts prognosis of Chinese colorectal cancer patients with liver metastases. Chin J Cancer . 2017; 36 (1): 78 PubMed Abstract | Publisher Full Text Competing Interests: No competing interests were disclosed. Reviewer Expertise: Pathology We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Brahimi M and Yassine B. Reviewer Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r227155 ) The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-227155 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 3 VERSION 3 PUBLISHED 28 Nov 2023 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 4 5 Version 3 (revision) 29 Aug 25 read Version 2 (revision) 29 Nov 24 read read Version 1 28 Nov 23 read read Maroua Brahimi , Centre hospitalier mohamed V, Safi, Morocco Belghali Yassine , Centre hospitalier universitaire mohamed VI, Marrakech, Morocco Luckshi Rajendran , University of Toronto, Toronto, Canada Christian Magyar , University Health Network (Ringgold ID: 7989), Toronto, Canada; Bern University Hospital, Bern, Switzerland Jacob Peoples , Queen's University, Kingston, Canada Mark Hull , Leeds Institute of Medical Research, University of Leeds, Leeds, UK Christian Sturesson , Karolinska University, Stockholm, Sweden Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Sturesson C. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 29 Sep 2025 | for Version 3 Christian Sturesson , Karolinska University, Stockholm, Sweden 0 Views copyright © 2025 Sturesson C. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The authors present an interesting study on the impact of neoadjuvant chemotherapy on survival after resection of colorectal liver metastases. Based on the histological response of chemotherapy, the authors show an association between survival and histological response, showing an advantage of the Rubbia-Brandt system. My biggest concern is that there are very few patients in each group making it difficult to draw firm conclusions about the causality of pathological response and survival. If the cohort was bigger, a multivariable analysis would also be needed to define which parameters influence survival. I'm afraid that the small number of patients make the results too unreliable. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise HBP-surgery I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Sturesson C. Peer Review Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.185719.r410779) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1523/v3#referee-response-410779 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Hull M. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 03 Jan 2025 | for Version 2 Mark Hull , Leeds Institute of Medical Research, University of Leeds, Leeds, UK 0 Views copyright © 2025 Hull M. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This is a small retrospective series of cases undergoing neo-adjuvant chemotherapy before CRCLM surgery. Cases were classified according to two published scoring systems for neo-adjuvant chemotherapy response. I did not find that the results provided a significant contribution to the field and the methods used are still unclear despite previous comments from other Reviewers. There was no CONSORT-style diagram explaining exclusions and number of CRCLM cases without neo-adjuvant treatment. I also could not access any Kaplan-Meier curves mentioned in amendments from V1. It is unclear about the profile of cases with conflicting information about the stage IV cases in the text and Abstract. A table may be helpful for the reader to interpret the range of TRG and Blazer scores. Several references are very old and could be updated. Similar to other reviewers, I could not understand how the ROC analysis was performed on scoring systems with >/= three grades. I suggest formal statistical review to confirm appropriateness and correct methodology for assessment of the scoring system characteristics. The statement about cases with lymph node metastasis was unclear. The Discussion is far too long and repeats many of the results. In parts, it reads like a narrative review of the literature. The Conclusion section does not contain any novel finding and the data provided do not support the statement that the Rubbia-Brandt TRG score can complement TN stage for improved survival prediction. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? No Competing Interests No competing interests were disclosed. Reviewer Expertise Trialist investigating pre-operative and adjuvant therapy in CRCLM resection surgery patients I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Hull M. Peer Review Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r353171) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-353171 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Peoples J. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 26 Dec 2024 | for Version 2 Jacob Peoples , Queen's University, Kingston, Canada 0 Views copyright © 2024 Peoples J. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The paper “Liver metastases from colorectal carcinoma: performance of pathological response scores” by Ben Slama et al. provides a comparison of two pathological response evaluation criteria for scoring response to neoadjuvant chemotherapy in patients undergoing hepatic resection for colorectal liver metastases—the Rubbia-Brandt score, and the Blazer scoring system. The scores are evaluated in terms of their prognostic ability in terms of overall survival after surgery. My primary concern about the study is that it lacks details that would aid in evaluating the results. In particular, I feel that the statistical analysis is described too briefly. The exact procedures used to conduct the statistical tests should be described, so that a reader could reproduce the analysis given the data table. For example, AUC is a metric for a binary outcome – what was the procedure for treating overall survival as binary? Likelihood ratios and RV scores are general tools that can be applied to many things in many ways. It should be described specifically how they are used to measure homogeneity and monotonicity in this context. On the topic of statistical analysis, why use AUC as a measure of discriminative ability rather than something more directly applicable to survival data such as the C-index? 1 I also want to raise a few possible reporting errors in the Study Characteristics section of the results: Under “Surgical treatment of liver metastases” it is stated that 63% were bilobar, and 37% uni-lobar. A few lines later, under “Pathological characteristics of liver metastases” it is stated that they were bi-lobar in 37% of cases (opposite of previous sentence). Please ensure all reported statistics are correct and internally consistent. Finally, I agree with many of the previous reviewers’ points, many of which are not yet addressed. These would include: A consort diagram would be helpful Include Kaplan-Meier curves of overall survival of entire cohort, as well as breakdown across different score categories so that the difference in separation between the two scoring systems can be visually compared? Much of the discussion feels irrelevant to the results of the paper. It would be better to have less survey-like content, and more discussion of how the findings of this paper add or contribute to the existing literature. Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? No If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes References 1. Harrell F: Evaluating the Yield of Medical Tests. JAMA: The Journal of the American Medical Association . 1982; 247 (18). Publisher Full Text Competing Interests No competing interests were disclosed. Reviewer Expertise medical image analysis, colorectal liver metastases I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Peoples J. Peer Review Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.171278.r345538) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1523/v2#referee-response-345538 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Rajendran L et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 21 May 2024 | for Version 1 Luckshi Rajendran , Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada Christian Magyar , Multi-Organ Transplant Program, University Health Network (Ringgold ID: 7989), Toronto, Ontario, Canada; Department of Visceral Surgery and Medicine, Bern University Hospital, Bern, Switzerland 0 Views copyright © 2024 Rajendran L et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This article by Ben Slama et al., provides a retrospective review of the performance of two prognostic scoring system based on assessment of pathologic response following neoadjuvant chemotherapy and liver resection for colorectal liver metastases. We would like to commend the authors for their efforts; however, we would like to raise the following points/ concerns: Abstract: 1. For the sex ratio, the comparator is needed, otherwise unable to deduce without assumption. Alternatively mentioning % of males (or alternatively females) could be considered. 2. Background and methods imply that all have tumors are stage IV (i.e. CRLM) – is 57% meant to indicate synchronous, and rest is metachronous? This is unclear/ inaccurate -should be rephrased. Similarly, the next sentence referencing “all stages combined” is confusing - these theoretically are all stage IV disease 3. Please incorporate statistical significance in comparison for survival estimates based on TRG1-5. Also, why do you use mean (overall?) survival and not median? 4. Please show 95%CI of the AUC. 5. Conclusions/Discussion section is missing in the abstract. Introduction: 1. Global disease burden (i.e. first sentence): we recommend to reference the original data source from WHO from the global cancer observatory 2. This paragraph needs to be proofread – grammar/ missing words, does not flow overall 3. Please add a statement on resectability considerations of CRLM, especially given only subset of patients are resection candidates 4. We recommend implementing guideline references (e.g. [Ref-1] ) and the original references for the neoadjuvant trials 5. The gap in knowledge statement needs to be rephrased, because of lack of accuracy. Methods: 1. Please include the different neoadjuvant chemotherapy treatment regimens and dosages. Additionally, RFA for CRLM is not considered a neoadjuvant treatment – it can be used in realm of curative. I would focus solely on neoadjuvant chemotherapy in this paper. Similarly use of HAIP may be a different population of patients with initially unresectable disease, can be confusing also when lumped in with population that received IV chemo alone 2. Please include last date of follow-up included. 3. Was normality of data distribution assessed? 4. Which statistical test were used to compare pathological responses? Please write in more detail about your diagnostic performance analysis, which tests were used? 5. For survival analysis we recommend to read [Ref-2,3]. Results: 1. How many left sided vs. right-sided tumours; Please also include other factors like presence of RAS mutation, BRAF status? 2. Is this all liver-only mets (i.e. extrahepatic mets excluded)? What is the percent of major vs. minor hepatectomy? What was done with the primary tumour in all of these cases? 3. Please consider including a CONSORT diagram, to allow the reader to assess the potential degree of selection bias, as you excluded patients based on ‘hospital records were unusable or could not be found, and cases with non-usable slides or tissue blocks’. 3. Same here as within the abstract, was 57% synchronous and 43% metachronous? Otherwise your selection criteria are not coherent. 4. Figure 1 and figure 2 are mixed up in the manuscript. Please fix 5. Consider reporting the T, N and M status of your cohort. 6. Please consider including the Kaplan Meier curve stratified by your regression grades. 7. Same here, why do you report mean survival and not median survival? Discussion: 1. Too long, reads like a review, please consider restricting it to what is related to this study. Consider restructuring into five paragraphs with: (1) key findings, (2) strengths and limitations, (3) comparison with similar research, (4) explanations of findings and (5) implications and actions needed. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? No If applicable, is the statistical analysis and its interpretation appropriate? No Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? No References 1. Cervantes A, Adam R, Roselló S, Arnold D, et al.: Metastatic colorectal cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol . 2023; 34 (1): 10-32 PubMed Abstract | Publisher Full Text 2. Clark TG, Bradburn MJ, Love SB, Altman DG: Survival analysis part I: basic concepts and first analyses. Br J Cancer . 2003; 89 (2): 232-8 PubMed Abstract | Publisher Full Text 3. Austin PC, Lee DS, Fine JP: Introduction to the Analysis of Survival Data in the Presence of Competing Risks. Circulation . 2016; 133 (6): 601-9 PubMed Abstract | Publisher Full Text Competing Interests No competing interests were disclosed. Reviewer Expertise clinical epidemiology, transplantation, liver cancer, surgery We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Rajendran L and Magyar C. Peer Review Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r278480) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-278480 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2023 Brahimi M et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 20 Dec 2023 | for Version 1 Maroua Brahimi , Laboratory of Pathology, Centre hospitalier mohamed V, Safi, Marrakech-safi, Morocco Belghali Yassine , Centre hospitalier universitaire mohamed VI, Marrakech, Marrakech, Morocco 0 Views copyright © 2023 Brahimi M et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions In the paper " Liver metastases from colorectal carcinoma: performance of pathological response scores", the authors evaluate the pathological response and compare the performance of two prognostic scores : Rubbia-Brandt tumor regression grade (TRG) and the Blazer scoring system, in a population of 70 patients with liver metastases from colorectal cancer . The conclusion is that the Rubbia-Brandt TRG was better in predicting survival, which is well known.The study is not novel and the aim of the study isn't contibutive to the field (1). Overall, the precision of the manuscript does not reach the acceptable standards, there are so many methodological errors: How the specimen was prepared? How the cases with more than one liver metastase were evaluated?.......(1), (2). Many sources of heterogenicity: for example all the histologic types were included....The statistical results lacks clarity and representativity (tables, figures...) (1). Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? No Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? No Are the conclusions drawn adequately supported by the results? Partly References 1. Rubbia-Brandt L, Giostra E, Brezault C, Roth AD, et al.: Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann Oncol . 2007; 18 (2): 299-304 PubMed Abstract | Publisher Full Text 2. Wang Y, Yuan YF, Lin HC, Li BK, et al.: Pathologic response after preoperative therapy predicts prognosis of Chinese colorectal cancer patients with liver metastases. Chin J Cancer . 2017; 36 (1): 78 PubMed Abstract | Publisher Full Text Competing Interests No competing interests were disclosed. Reviewer Expertise Pathology We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Brahimi M and Yassine B. Peer Review Report For: Rubbia-Brandt vs Blazer scores for survival prediction in colorectal liver metastases after chemotherapy [version 3; peer review: 5 not approved] . F1000Research 2025, 12 :1523 ( https://doi.org/10.5256/f1000research.148808.r227155) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1523/v1#referee-response-227155 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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